
There is another equivalent geometric definition for star sets and star complements. Let G
be a graph with vertex set V(G) = {1, . . . , n}and adjacency matrix A. Let {e1, . . . , en}be the
standard orthonormal basis of Rn,µbe an eigenvalue of G, and Pbe the matrix which represents
the orthogonal projection of Rnonto the eigenspace E(µ) = {x∈Rn:A(G)x=µx }of Awith
respect to {e1, . . . , en}. Since E(µ) is spanned by the vectors P ej(j= 1, . . . , n), there exists
X⊆V(G) such that the vectors P ej(j∈X) form a basis for E(µ). Such a subset Xof V(G) is
called a star set for µin G. In this situation H=G−Xis called a star complement for µ.
For any graph Gof order nwith distinct eigenvalues λ1, . . . , λm, there exists a partition V(G) =
X1S···SXmsuch that Xiis a star set for eigenvalue λi(i= 1, . . . , m). Such a partition is called
astar partition of G. For any graph G, there exists at least one star partition ([10]). Each star
partition determines a basis for Rnconsisting of eigenvectors of an adjacency matrix. It provides
a strong link between graph structure and linear algebra.
There are a lot of literatures about using star complements to construct and characterize
certain graphs([1,2,3,8,12,14,16,18,19,20,21,22,23,24,25]), especially, regular graphs
with a prescribed graph such as K1,s,K1OhKq,K2,5,K2,s,K1,1,t,K1,1,1,t,sK1∪Kt,Pt(µ= 1),
Kr,r,r (µ= 1) or Kr,s +tK1(µ= 1) as a star complement were well studied in the literature.
Motivated by the above research, in this paper, we introduce the fundamental properties of the
theory of star complements in Section 2, study the regular graphs with the bipartite graph Kt,s (s≥
t≥1) as a star complement for an eigenvalue µin Section 3, completely characterize the regular
graphs with K3,s (s≥3) as a star complement for an eigenvalue µin Section 4, study some
properties of Ks,s in Section 5, and propose some problems for further research.
2 Preliminaries
In this section, we introduce some results of star sets and star complements that will be re-
quired in the sequel. The following fundamental result combines the Reconstruction Theorem ([7,
Theorem 7.4.1]) with its converse ([7, Theorem 7.4.4]).
Theorem 2.1. ([7]) Let µbe an eigenvalue of Gwith multiplicity k,Xbe a set of vertices in the
graph G. Suppose that Ghas adjacency matrix
AXBT
B C ,
2